{"id":"W2118775665","doi":"10.1177/1475921714546063","title":"A technique for real-time detecting, locating, and quantifying damage in large polymer composite structures made of carbon fibers and carbon nanotube networks","year":2014,"lang":"en","type":"article","venue":"Structural Health Monitoring","topic":"Smart Materials for Construction","field":"Environmental Science","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Epoxy; Composite material; Materials science; Composite number; Carbon nanotube; Durability; Polymer; Structural health monitoring","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005329624,0.0002113347,0.0003682114,0.0000893968,0.0002046854,0.00002901366,0.0001034542,0.0001262243,0.000004663126],"category_scores_gemma":[0.00003435083,0.0002065702,0.00002660955,0.0001536127,0.0001351214,0.0001059775,0.0001486786,0.0001616853,8.268795e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001664514,"about_ca_system_score_gemma":0.00001200125,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.013698,"about_ca_topic_score_gemma":0.0005625237,"domain_scores_codex":[0.9983723,0.0001384193,0.0004530825,0.0003889956,0.0001620463,0.0004852037],"domain_scores_gemma":[0.9992653,0.000109561,0.0003067028,0.0001925299,0.000009377946,0.0001165449],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004860833,0.000001671317,0.6404964,0.0001482266,0.000004286195,3.55627e-7,0.000442537,0.0002045477,0.3548265,0.00002280877,3.98628e-7,0.003803673],"study_design_scores_gemma":[0.0005835631,0.0001547546,0.7948583,0.0002235655,0.00001090814,0.00002870608,0.0001605789,0.01310774,0.1903874,0.0002455444,0.000004435971,0.0002344293],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985036,0.0001926749,0.00008511905,0.0000254518,0.000498413,0.0005956174,0.000005451158,0.00004626744,0.00004735116],"genre_scores_gemma":[0.9942479,0.00003560144,0.005476174,0.000009604885,0.0001613413,0.00003123505,0.000003519412,0.00002980306,0.000004818729],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1644391,"threshold_uncertainty_score":0.9928699,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01162310729869953,"score_gpt":0.2765001784599181,"score_spread":0.2648770711612186,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}